Reliable traffic congestion and traffic accident data is essential for the development of efficient urban traffic operation and management. The adverse effects of traffic incidents can be reduced by implementing automatic traffic state detection. Rapid discrimination of the traffic state plus the use of traffic flow guidance and traffic control can overall minimize adverse effects of traffic congestion in the road network.
Traditionally, traffic data is determined based on an analysis of data collected by various sensor devices installed at fixed locations on a road or installed within a probe vehicle travelling on the road. For example, a traffic incident can be detected using the occupancy data from two adjacent detectors. However, utilization of fixed detectors can be extremely expensive, especially in larger areas. In another example, a freeway traffic incident detection algorithm based on probe vehicles (e.g., vehicles that collect data from a traffic stream to which they belong) can be utilized for detection of the traffic incident. The freeway traffic incident detection algorithm is based on a bivariate analysis model using two variables: the average travel time of probe vehicles, and the difference of travel times between two adjacent time intervals.
To predict highway traffic density, some of the conventional systems utilize a Kalman filtering technique (KFT) that employs linear quadratic estimation to predict traffic density. Further, a few conventional systems employ a panoramic video-based method to detect traffic states, while others utilize a cluster analysis with information received from ground detectors to realize traffic state classification. Furthermore, some other conventional systems also utilize a model of K-nearest neighbors nonparametric regression for traffic state forecasting, wherein the graded traffic state forecasting of different time intervals is carried out using the field traffic flow data. However, these conventional approaches for detection of traffic data and/or classification of traffic states can be time consuming, leading to traffic congestion and/or unsafe driving conditions.